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Learning Rapid Turning, Aerial Reorientation, and Balancing using Manipulator as a Tail

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arxiv 2407.10420 v1 pith:PTA3KNFP submitted 2024-07-15 cs.RO cs.AI

classification cs.ROcs.AI
keywords manipulatorrobotstailquadrupedtailsaerialbalancingcapabilities
verification ladder T0 review T1 audit T2 compute T3 formal
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In this research, we investigated the innovative use of a manipulator as a tail in quadruped robots to augment their physical capabilities. Previous studies have primarily focused on enhancing various abilities by attaching robotic tails that function solely as tails on quadruped robots. While these tails improve the performance of the robots, they come with several disadvantages, such as increased overall weight and higher costs. To mitigate these limitations, we propose the use of a 6-DoF manipulator as a tail, allowing it to serve both as a tail and as a manipulator. To control this highly complex robot, we developed a controller based on reinforcement learning for the robot equipped with the manipulator. Our experimental results demonstrate that robots equipped with a manipulator outperform those without a manipulator in tasks such as rapid turning, aerial reorientation, and balancing. These results indicate that the manipulator can improve the agility and stability of quadruped robots, similar to a tail, in addition to its manipulation capabilities.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Reinforcement Learning from Wild Animal Videos

    cs.RO 2024-12 conditional novelty 6.0 of 10

    A quadruped robot acquires walking, jumping, running-like, and standing skills using only the output of a video classifier trained on wild-animal videos as its reinforcement learning reward.

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